A pose-independent method for 3D face landmark formalization

Recently, 3D landmark extraction has been widely researched and experimented in medical field, for both corrective and aesthetic purposes. Automation of these procedures on three-dimensional face renderings is something desirable for the specialists who work in this field. In this work we propose a new method for accurate landmark localization on facial scans. The method relies on geometrical descriptors, such as curvatures and Shape Index, for computing candidate and initial points, and on a statistical model based on Procrustes Analysis and Principal Component Analysis, which is fitted to candidate points, for extracting the final landmarks. The elaborated method is independent on face pose.